A CNN Based Structured Light Communication Scheme for Internet of Underwater Things Applications

Abderrahmen Trichili; Chaouki Ben Issaid; Boon S. Ooi; Mohamed-Slim Alouini

doi:10.1109/JIOT.2020.2988979

A CNN Based Structured Light Communication Scheme for Internet of Underwater Things Applications

Abderrahmen Trichili, Chaouki Ben Issaid, Boon S. Ooi, Mohamed-Slim Alouini

Research output: Contribution to journal › Article › peer-review

22 Scopus citations

Abstract

Underwater optical wireless communication is an emerging field that can provide reliable connectivity for future generation internet of underwater things devices. In this paper, we propose a communication system based on single and superposition of Laguerre Gaussian modes to transfer information and rely on a convolutional neural network for the mode identification in an underwater environment. A 100% recovery fidelity is reported at clear and turbid water. Beyond 90% of identification, accuracy is achieved under different laboratory-emulated underwater turbulence conditions. The practical implementation of the proposed spatial-mode based communication scheme is further discussed.

Original language	English (US)
Pages (from-to)	1-1
Number of pages	1
Journal	IEEE Internet of Things Journal
DOIs	https://doi.org/10.1109/JIOT.2020.2988979
State	Published - 2020

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: The authors would like to thank Andrea Bertoncini for the experimental setup illustration and the fruitful discussions.

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10.1109/JIOT.2020.2988979

https://repository.kaust.edu.sa/bitstream/10754/662568/1/Accepted_A_New_CNN_based_Communication_Scheme_for_Underwater_Internet_of_Things_Applications__KaustRepisotry.pdf

Cite this

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title = "A CNN Based Structured Light Communication Scheme for Internet of Underwater Things Applications",

abstract = "Underwater optical wireless communication is an emerging field that can provide reliable connectivity for future generation internet of underwater things devices. In this paper, we propose a communication system based on single and superposition of Laguerre Gaussian modes to transfer information and rely on a convolutional neural network for the mode identification in an underwater environment. A 100% recovery fidelity is reported at clear and turbid water. Beyond 90% of identification, accuracy is achieved under different laboratory-emulated underwater turbulence conditions. The practical implementation of the proposed spatial-mode based communication scheme is further discussed.",

author = "Abderrahmen Trichili and {Ben Issaid}, Chaouki and Ooi, {Boon S.} and Mohamed-Slim Alouini",

note = "KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: The authors would like to thank Andrea Bertoncini for the experimental setup illustration and the fruitful discussions.",

year = "2020",

doi = "10.1109/JIOT.2020.2988979",

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AU - Trichili, Abderrahmen

AU - Ben Issaid, Chaouki

AU - Ooi, Boon S.

AU - Alouini, Mohamed-Slim

N1 - KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: The authors would like to thank Andrea Bertoncini for the experimental setup illustration and the fruitful discussions.

PY - 2020

Y1 - 2020

N2 - Underwater optical wireless communication is an emerging field that can provide reliable connectivity for future generation internet of underwater things devices. In this paper, we propose a communication system based on single and superposition of Laguerre Gaussian modes to transfer information and rely on a convolutional neural network for the mode identification in an underwater environment. A 100% recovery fidelity is reported at clear and turbid water. Beyond 90% of identification, accuracy is achieved under different laboratory-emulated underwater turbulence conditions. The practical implementation of the proposed spatial-mode based communication scheme is further discussed.

AB - Underwater optical wireless communication is an emerging field that can provide reliable connectivity for future generation internet of underwater things devices. In this paper, we propose a communication system based on single and superposition of Laguerre Gaussian modes to transfer information and rely on a convolutional neural network for the mode identification in an underwater environment. A 100% recovery fidelity is reported at clear and turbid water. Beyond 90% of identification, accuracy is achieved under different laboratory-emulated underwater turbulence conditions. The practical implementation of the proposed spatial-mode based communication scheme is further discussed.

UR - http://hdl.handle.net/10754/662568

UR - https://ieeexplore.ieee.org/document/9075290/

U2 - 10.1109/JIOT.2020.2988979

DO - 10.1109/JIOT.2020.2988979

M3 - Article

SN - 2372-2541

SP - 1

EP - 1

JO - IEEE Internet of Things Journal

JF - IEEE Internet of Things Journal

ER -

A CNN Based Structured Light Communication Scheme for Internet of Underwater Things Applications

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